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The Effects of Swine Coronaviruses on ER Stress, Autophagy, Apoptosis, and Alterations in Cell Morphology

Swine coronaviruses include the following six members, namely porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine delta coronavirus (PDCoV), swine acute diarrhea syndrome coronavirus (SADS-CoV), porcine hemagglutinating encephalomyelitis virus (PHEV), and porcine respiratory coronavirus (PRCV). Clinically, PEDV, TGEV, PDCoV, and SADS-CoV cause enteritis, whereas PHEV induces encephalomyelitis, and PRCV causes respiratory disease. Years of studies reveal that swine coronaviruses replicate in the cellular cytoplasm exerting a wide variety of effects on cells. Some of these effects are particularly pertinent to cell pathology, including endoplasmic reticulum (ER) stress, unfolded protein response (UPR), autophagy, and apoptosis. In addition, swine coronaviruses are able to induce cellular changes, such as cytoskeletal rearrangement, alterations of junctional complexes, and epithelial-mesenchymal transition (EMT), that render enterocytes unable to absorb nutrients normally, resulting in the loss of water, ions, and protein into the intestinal lumen. This review aims to describe the cellular changes in swine coronavirus-infected cells and to aid in understanding the pathogenesis of swine coronavirus infections. This review also explores how the virus exerted subcellular and molecular changes culminating in the clinical and pathological findings observed in the field.

ER Stress
The endoplasmic reticulum (ER) in the cytoplasm of eukaryotic cells is responsible for protein synthesis and folding. ER stress is a condition in which ER homeostasis is disrupted, resulting in the accumulation of unfolded or misfolded proteins in the ER. Various physiological and pathologic factors can induce ER stress, such as gene mutations, hypoxia, nutrient deprivation, cell injury, and pathogen infection [9]. Cells initiate the unfolded protein response (UPR) to restore ER homeostasis [10]. Through a series of signal transduction pathways, the UPR removes aberrant proteins by inhibiting protein translation, increasing protein folding capacity, and promoting ER-associated degradation (ERAD) [11]. Three protein sensors, namely pancreatic ER eIF2α kinase (PERK), activating transcription factor 6 (ATF6), and inositol-requiring transmembrane kinase/endonuclease 1 (IRE1), play critical roles in the UPR [11].
In the homeostatic ER, PERK, ATF6, and IRE1 are connected to the ER membrane by the ER chaperone glucose-regulated protein 78 (GRP78, also known as BiP) [11]. When the ER is stressed, GRP78 dissociates from the intraluminal domains of sensors into the ER lumen and activates these three proteins. Among the three sensors, PERK is activated firstly. Activated PERK phosphorylates the α subunit of eukaryotic translation initiation factor 2 (eIF2α), followed by the translation of activating transcription factor 4 (ATF4). As a transcription factor, ATF4 regulates genes involved in protein folding and the oxidative stress response. Second, activated ATF6 moves from the ER into the nucleus and stimulates UPR genes, resulting in elevated expression of X-box binding protein 1 (XBP1) and GRP78. As a result, an increased amount of GRP78 is considered the hallmark of ER stress and UPR [12]. Later, activated IRE1 splices XBP1 mRNA to generate a functionally active isoform of XBP1 (XBP1s), which is a transcription factor that regulates most UPR-associated genes [13]. Additionally, ER stress is associated with autophagy ( Figure 3), which contributes to removing unnecessary or dysfunctional cellular components. For example, IRE1 is required for autophagy activation [14]. Therefore, the UPR induces a pro-survival adaptation via the PERK, ATF6, and IRE1 pathways.
When ER stress is persistently unresolved, cells may undergo apoptosis or chronic ER stress (Figure 3). Apoptosis is a type of programmed cell death, and ER stress-induced apoptosis is responsible for eliminating cells under irremediable ER stress. For example, ATF4 upregulates C/EBP homologous protein (CHOP), which is a proapoptotic transcription factor [15]. The relationship between apoptosis and infection of swine coronaviruses is described in the section "Apoptosis in Swine CoV Infection" below. On the other hand, stressed but surviving cells can manage protein synthesis and adapt to chronic ER stress. For example, neoplastic cells under ER stress persistently express an elevated GRP78 level to adapt to a hostile microenvironment [16]. One of the cellular alterations associated with chronic ER stress is the epithelial-mesenchymal transition (EMT), which is described in the section "Cellular Morphologic Alterations in Swine CoV Infection" below.  (Table 2). Swine coronaviruses may either induce or inhibit autophagy. These changes further evolve into degeneration, loss of host cells, necrosis, and inflammation. Furthermore, chronic alteration in cell morphology induces epithelial-mesenchymal transition (EMT). Some of these molecular and subcellular changes can be appreciated in vivo by pathological examination of tissues from infected swine, while others are found only in in vitro settings and remain to be found in clinical specimens (Table 1).

ER Stress in Swine CoV Infection
As RNA viruses, CoVs replicate in the cytoplasm of host cells, and viral proteins are mainly assembled in the ER. CoVs form double-membrane vesicles (DMVs) and convoluted membranes (CMs), which directly arise from the ER and the Golgi complex [17]. CoVs also acquire lipid envelopes from host cells when the viral nucleocapsid buds from the endoplasmic reticulum-Golgi intermediate compartment (ERGIC). These processes induce the depletion of the ER membrane and disrupt ER morphology and function, leading to ER stress [18] ( Table 2). The production of viral transmembrane glycoproteins, such as the 3a protein of severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), also leads to ER stress [19]. For now, SARS-CoVs are well known for their pandemic threat to  (Table 2). Swine coronaviruses may either induce or inhibit autophagy. These changes further evolve into degeneration, loss of host cells, necrosis, and inflammation. Furthermore, chronic alteration in cell morphology induces epithelialmesenchymal transition (EMT). Some of these molecular and subcellular changes can be appreciated in vivo by pathological examination of tissues from infected swine, while others are found only in in vitro settings and remain to be found in clinical specimens (Table 1).
When ER stress is persistently unresolved, cells may undergo apoptosis or chronic ER stress ( Figure 3). Apoptosis is a type of programmed cell death, and ER stress-induced apoptosis is responsible for eliminating cells under irremediable ER stress. For example, ATF4 upregulates C/EBP homologous protein (CHOP), which is a proapoptotic transcription factor [15]. The relationship between apoptosis and infection of swine coronaviruses is described in the section "Apoptosis in Swine CoV Infection" below. On the other hand, stressed but surviving cells can manage protein synthesis and adapt to chronic ER stress. For example, neoplastic cells under ER stress persistently express an elevated GRP78 level to adapt to a hostile microenvironment [16]. One of the cellular alterations associated with chronic ER stress is the epithelial-mesenchymal transition (EMT), which is described in the section "Cellular Morphologic Alterations in Swine CoV Infection" below.

ER Stress in Swine CoV Infection
As RNA viruses, CoVs replicate in the cytoplasm of host cells, and viral proteins are mainly assembled in the ER. CoVs form double-membrane vesicles (DMVs) and convoluted membranes (CMs), which directly arise from the ER and the Golgi complex [17]. CoVs also acquire lipid envelopes from host cells when the viral nucleocapsid buds from the endoplasmic reticulum-Golgi intermediate compartment (ERGIC). These processes induce the depletion of the ER membrane and disrupt ER morphology and function, leading to ER stress [18] ( Table 2). The production of viral transmembrane glycoproteins, such as the 3a protein of severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), also leads to ER stress [19]. For now, SARS-CoVs are well known for their pandemic threat to humans. Studies have demonstrated that SARS-CoV-2 induces DMVs, zippered ER, ER stress, and UPR through all three UPR pathways [20][21][22]. Zippered ER is a rearrangement that forms a paired ER membrane with double-membrane spherules.
During viral replication, CoVs shut down cellular translation to benefit the synthesis of viral products. For example, viral N protein can interact with elongation factor 1α (EF1α), a major translation factor, leading to translational suppression [23]. It has also been reported that SARS-CoV-2 can modulate the expression of RNAs and proteins in host cells [24]. To assess the variances in virus-infected cells, scientists applied gene expression profiling and mass spectrometry, which can detect differentially expressed genes (DEGs) and differentially expressed proteins (DEPs), respectively. DEGs are a broad group, and common detectable DEGs include RNA, microRNA (miRNA), circular RNA (circRNA), and messenger RNA (mRNA).
Recently, it has been demonstrated that PEDV induces reactive oxygen species (ROS)dependent ER stress via the PERK and IRE1 pathways in Vero cells [27]. Interestingly, the mutation in the PEDV E protein enhances ER stress and apoptosis in Vero cells [28]. In intestinal epithelial cells (IECs), the E and N proteins but not the M protein of PEDV lead to ER stress [29][30][31]. PEDV upregulates DEGs that transport proteins between ER and Golgi compartments in intestinal porcine epithelial cell line-J2 (IPEC-J2) cells [32,33]. In human embryonic kidney (HEK) 293T cells, PEDV ORF3 protein upregulates GRP78 and later activates the PERK-eIF2α signaling pathway and autophagy [34].  [20][21][22]. Zippered ER is a rearrangement that forms a paired ER membrane with double-membrane spherules. During viral replication, CoVs shut down cellular translation to benefit the synthesis of viral products. For example, viral N protein can interact with elongation factor 1α (EF1α), a major translation factor, leading to translational suppression [23]. It has also been reported that SARS-CoV-2 can modulate the expression of RNAs and proteins in host cells [24]. To assess the variances in virus-infected cells, scientists applied gene expression profiling and mass spectrometry, which can detect differentially expressed genes (DEGs) and differentially expressed proteins (DEPs), respectively. DEGs are a broad group, and common detectable DEGs include RNA, microRNA (miRNA), circular RNA (circRNA), and messenger RNA (mRNA).
In eight-week-old weaned pigs, PEDV induces ER stress and UPR in jejunal epithelial cells through all three UPR pathways [25] (Figure 4, Table 2). In Vero cells, PEDV facilitates ER membrane rearrangement, ER stress, and UPR via the PERK and ATF6 pathways [17,26]. Recently, it has been demonstrated that PEDV induces reactive oxygen species (ROS)-dependent ER stress via the PERK and IRE1 pathways in Vero cells [27]. Interestingly, the mutation in the PEDV E protein enhances ER stress and apoptosis in Vero cells [28]. In intestinal epithelial cells (IECs), the E and N proteins but not the M protein of PEDV lead to ER stress [29][30][31]. PEDV upregulates DEGs that transport proteins between ER and Golgi compartments in intestinal porcine epithelial cell line-J2 (IPEC-J2) cells [32,33]. In human embryonic kidney (HEK) 293T cells, PEDV ORF3 protein upregulates GRP78 and later activates the PERK-eIF2α signaling pathway and autophagy [34]. The infection of TGEV induces ER stress and UPR via all three UPR pathways [35]. The TGEV N protein alone induces ER stress in porcine intestinal epithelial cells, while nonstructural protein 7 (nsp7) does not increase GRP78 expression [36,37]. Interestingly, the UPR suppresses the replication of TGEV in swine testicular (ST) and IPEC-J2 cells through the PERK-eIF2α axis [35]. On the other hand, IRE1 facilitates TGEV replication by downregulating type I interferon (IFN), which is a critical antiviral signaling protein [38].
Similar to other CoVs, PDCoV upregulates the protein level of GRP78 and induces DMVs and zippered ER formation [39,40]. A recent study has demonstrated that PDCoV induces ER stress through all three UPR pathways [41]. Few studies focus on SADS-CoV. The infection of TGEV induces ER stress and UPR via all three UPR pathways [35]. The TGEV N protein alone induces ER stress in porcine intestinal epithelial cells, while nonstructural protein 7 (nsp7) does not increase GRP78 expression [36,37]. Interestingly, the UPR suppresses the replication of TGEV in swine testicular (ST) and IPEC-J2 cells through the PERK-eIF2α axis [35]. On the other hand, IRE1 facilitates TGEV replication by downregulating type I interferon (IFN), which is a critical antiviral signaling protein [38].
Similar to other CoVs, PDCoV upregulates the protein level of GRP78 and induces DMVs and zippered ER formation [39,40]. A recent study has demonstrated that PDCoV induces ER stress through all three UPR pathways [41]. Few studies focus on SADS-CoV. SADS-CoV enhances the stress-associated RNA expression in IPEC-J2 cells, implying the possibility of disrupted ER homeostasis [42].
Differ from enteric coronaviruses, PHEV replicates in the cell bodies of neurons, and viral particles bud from the ERGIC [43]. PHEV also induces ER stress and all three branches of the UPR pathway both in vivo and in vitro [44]. Interestingly, Rab3a, a Golgi-associated protein, can act as a regulator of PHEV replication, indicating the close relationship between ERGIC and viral replication [45]. There is no published research focused on ER stress in PRCV infection at this time.
In addition to reinstatement of ER homeostasis, the UPR can modulate viral replication and the host's innate response. The UPR suppresses PHEV replication via the PERK/PKR-eIF2α pathways [44]. PERK signaling also suppresses the replication of PEDV and TGEV [26,35]. Unsurprisingly, viruses have evolved strategies to counteract the UPR. For example, TGEV protein 7 accelerates eIF2α dephosphorylation to counteract host defense [46].
Stressed cells form stress granules (SGs), which are nonmembranous cytosolic RNA granules generated within the cytoplasm and closely associated with phosphorylated eIF2α [47]. The fundamental components of SGs are Ras-GTPase-activating protein-binding protein 1 (G3BP1), T-cell intracellular antigen 1 (TIA1), and poly(A) binding protein (PABP). It has been demonstrated that PHEV induces transient SG formation in the late stages of infection [44]. Increasing evidence suggests that SGs have the antiviral ability to limit viral replication. For instance, G3BP1 impairs PEDV replication in Vero cells [48]. However, PEDV suppresses the formation of SGs by inducing caspase-8-mediated G3BP1 cleavage [49]. Caspases are involved in apoptosis and discussed in the "Apoptosis in Swine CoV Infection" section.

Autophagy in Swine CoV Infection
Autophagy is a self-degradative and highly regulated process in response to balance energy sources. Autophagy is also essential for removing misfolded or aggregated proteins, clearing damaged organelles, and eliminating intracellular pathogens [91]. Initially, the phagophore, an isolated membrane, engulfs cytosolic components and sequesters the intracellular cargo into an autophagosome. The autophagosome, a double-membrane vesicle, later fuses with lysosomes, promoting proteolytic degradation of cytosolic components. The autophagy-related complex consists of ULK1 protein kinases, autophagy-related gene 5 (Atg5)-Atg12 conjugation system, light chain 3 (LC3) conjugation system, adaptor protein p62/SQSTM1, and ubiquitinated proteins. Beclin-1 (BECN1) at the ER and other membranes contribute to phagophore formation [91]. It has been shown that SARS-CoV-2 induces autophagy because of excessive oxidative stress and ER stress [20]. The nsp6 protein of infectious bronchitis virus (IBV), an avian coronavirus, can also trigger autophagy [92]. Moreover, the attenuation of autophagy reduces SARS-CoV-1 and coronavirus mouse hepatitis virus (MHV) infection [93,94].
Whether swine CoVs inhibit or "hijack" autophagy for in vivo viral replication remains unclear (Table 2, Figure 5). PEDV, TGEV, PDCoV, and PHEV may induce autophagy to benefit viral replication [50,66,79,85]. PEDV leads to autophagy in Vero cells, and silence of the BECN1 or ATG5 gene reduces the viral titer, suggesting a potential profit from autophagy [50]. Additionally, the PEDV nsp6 protein induces autophagy by inhibiting the PI3K/Akt/mTOR pathway, which promotes cell death and attenuates autophagy [51,52]. In Vero cells, PEDV ORF3 protein induces the conversion of LC3-I to LC3-II, followed by autophagy. Moreover, the process is impaired by an ER stress inhibitor, indicating that PEDV ORF3 protein-induced autophagy is dependent on the ER stress [34]. Notably, PEDV induces autophagy in Vero cells via both the PERK and IER1 pathways, illustrating the relationship between ER stress and autophagy [27]. In ST cells, PEDV regulates miRNA and mRNA associated with the PI3K-Akt signaling pathway, implying the manipulation of autophagy [53]. In HEK293T cells, knockdown of the BECN1 gene decreases the PEDV replication [54]. Interestingly, autophagy can promote immunological defense mechanisms to counteract viral infection [95]. For instance, BECN1 negatively regulates the immune response by preventing excessive production of IFN [96]. As a result, PEDV negatively regulates the IFN pathway by inducing autophagy [54]. In vivo study has demonstrated that TGEV facilitates mitophagy, a selective autophagy in mitochondria, to counteract oxidative stress and apoptosis, suggesting that autophagy benefits viral replication [66]. Interestingly, doxycycline can induce mitophagy and  In vivo study has demonstrated that TGEV facilitates mitophagy, a selective autophagy in mitochondria, to counteract oxidative stress and apoptosis, suggesting that autophagy benefits viral replication [66]. Interestingly, doxycycline can induce mitophagy and facilitates TGEV replication [97]. PDCoV leads to autophagosome-like vesicles and autophagy by activating both LC3 I/II and p62 [79]. PDCoV also regulates DEPs involved in the PI3K/AKT/mTOR signaling pathway in porcine intestinal epithelial cells [98]. PHEV promotes ULK1-independent autophagy in mouse neuro-2a (N2a) cells, which is regulated by BECN1 [85]. Interestingly, PHEV induces autophagy but blocks the fusion of phagosomes and lysosomes to benefit viral replication [86]. PHEV also facilitates transcription factor EB (TFEB) to promote autophagosome formation [99]. It has been suggested that lysosomal dysfunction and defects in fusion are involved in the pathogenesis of PHEV infection [100].
Nevertheless, there are controversial data regarding the role of autophagy in swine CoV infection. MYH1485, an autophagy inhibitor, enhances the PEDV infection rate in Vero E6 cells [58]. Rapamycin, an autophagy inducer, impairs the infectivity of PEDV, TGEV, and PHEV but increases the expression of PDCoV [86,[101][102][103]. In addition, genetic inhibition by knockdown of LC3, ATG5, and ATG7 demonstrates that TGEV replication is negatively regulated by autophagy [102]. SADS-CoV upregulates DEGs associated with the autophagy pathway in IPEC-J2 cells but downregulates them in Vero E6 cells [42,104]. No study has focused on the relationship between PRCV and cellular autophagy.

Apoptosis in Swine CoV Infection
Apoptosis is a process of programmed cell death, and apoptotic cells are morphologically characterized by condensed nuclei, fragmented DNA, and cellular shrinkage. The essential regulator of apoptosis is caspases, which are a family of proteolytic enzymes, and myriad proapoptotic and antiapoptotic proteins regulate the activity of apoptosis [91]. For instance, p53 is a proapoptotic protein involved in the gene transcription of DNA repair and cell cycle arrest. In contrast to caspase-dependent apoptosis, caspase-independent apoptosis is induced by released mitochondrial proteins or lysosomal membrane permeabilization [105]. For example, apoptosis-inducing factor (AIF), a mitochondrial protein, induces caspase-independent apoptosis by translocating from the mitochondrial intermembrane space to the nucleus [106].
Apoptosis is initiated by the FasL-(extrinsic) and mitochondria-(intrinsic) mediated pathways [107]. The extrinsic pathway involves cell surface death receptors, such as the tumor necrosis factor (TNF) receptor gene superfamily or Fas (CD95). On the other hand, the intrinsic pathway is activated by nonreceptor-mediated stimuli that produce intracellular signals and permeabilize the mitochondrial outer membrane. As mentioned previously, prolonged ER stress triggers ER stress-dependent apoptosis via the p38 mitogenactivated protein kinase (MAPK) signaling pathway [108].
The infection of CoVs induces apoptosis through complex mechanisms, and apoptosis has different effects on viral replication. For instance, SARS-CoV-2 induces apoptosis via the extrinsic pathway [109]. Apoptosis can facilitate viral release and dissemination from infected cells. On the other hand, inhibition of apoptosis prevents premature cell death, allowing viral replication. CoVs can regulate the MAPK signaling pathway to facilitate viral replication. For example, PEDV and PDCoV manipulate the JNK1/2 and p38/MAPK pathways to benefit viral biosynthesis and regulate immune responses [110,111].
The infection of PEDV facilitates apoptosis (Table 2, Figure 6) through many different mechanisms. In vivo studies have demonstrated that PEDV induces apoptosis, enterocyte proliferation, and a reduced ratio of villus height to crypt depth in nursing and weaned piglets [25,55,56]. In Vero cells, PEDV induces apoptosis by the p53-PUMA signaling pathway but not by the p38 MAPK or SAPK/JNK signaling pathways, and apoptosis is evidenced by activated proapoptotic protein p53 and oxidative stress [57,112]. PEDV also elevates the expression of DEGs associated with apoptosis, the p53 signaling pathway, and the MAPK signaling pathway in Vero cells [57,58]. PEDV facilitates both caspaseindependent and caspase-dependent apoptosis. In PEDV-infected Vero cells, AIF and AIF-associated DEPs activate caspase-independent apoptosis [55,57,59], while caspase-8 and -3 activate the caspase-dependent pathway [60]. Compared to the activation of caspase-3 by both extrinsic and intrinsic apoptotic pathways, caspase-8 is the initiator caspase of extrinsic apoptosis only. Interestingly, PEDV downregulates caspase-8 protein in early viral infection, suggesting a benefit for viral replication [59,113]. As mentioned in the "ER Stress in Swine CoV Infection" section, PEDV utilizes caspase-8 to cleave G3BP1,a component of stress granules, to promote viral replication in Vero cells [49]. These findings elucidate a complex relationship among PEDV, ER stress, and apoptosis. Caspase-6 and -7 also cleave PEDV N protein at the late stage of viral replication in Vero cells, but the role of cleavage in viral pathogenicity remains unclear [114]. In Vero cells, PEDV S protein is a critical inducer of apoptosis [115], while ORF3 protein inhibits apoptosis to enhance viral proliferation [116]. The ORF3 protein of PEDV has no effect on apoptosis in HEK293T cells [34]. PEDV also facilitates apoptosis in IECs [61], and apoptosis in IPEC-J2 cells is associated with the PI3K/AKT/mTOR pathway [62,63]. PEDV increases the expression of circRNAs and DEPs involved in apoptosis in IPEC-J2 cells [33,63]. In Vero cells and jejunum of piglets, PEDV induces the expression of interleukin-11 (IL-11), which is antiapoptotic and likely inhibits viral replication [117]. In brief, TGEV induces apoptosis via p53 and ROS, subsequently activating th MAPK signaling pathway. As a result, this pathway activates both extrinsic and int pathways as well as both caspase-dependent and caspase-independent pathways [68 TGEV damages mitochondria by upregulating cellular miRNA-4331, resulting i opening of the mitochondrial permeability transition pore (mPTP) and subsequen mitochondrial permeability [67,75]. TGEV also downregulates miRNA-27b, which sponsible for inhibiting apoptosis [118]. Similar to PEDV, the TGEV N protein is cle by caspase-6 and -7 during apoptosis [74]. It is controversial whether the N prote TGEV located in mitochondria induces mitochondrial injury [66,119]. Interestingly, T protein 7 inhibits apoptosis [46]. Host cells have developed strategies to eliminat damage. For example, miRNA-222 in porcine kidney (PK-15) cells as well as mitop and circRNA circEZH2 in IPEC-J2 cells regulate the mitochondrial dysfunction d TGEV infection [66,67,120]. p53 inhibits TGEV replication via IFN signaling and prom cell cycle arrest at the S and G2/M phases [72,121,122]. In vitro studies demonstrat TGEV induces apoptosis in ST cells and PK-15 cells but not in intestinal epithelial [66,70,73,82,123]. As mentioned previously, TGEV induces autophagy to suppress o tive stress and apoptosis but benefit viral infection in IPEC-J2 cells [66]. In addition, T facilitates pyroptosis, which is a highly inflammatory form of programmed cell dea IPEC-J2 cells [124].
In vivo study shows that PDCoV induces apoptosis via the p38/MAPK sign pathway in the small intestine of 7-day-old piglets [80]. In addition, PDCoV induces a In brief, TGEV induces apoptosis via p53 and ROS, subsequently activating the p38 MAPK signaling pathway. As a result, this pathway activates both extrinsic and intrinsic pathways as well as both caspase-dependent and caspase-independent pathways [68][69][70][71][72][73][74]. TGEV damages mitochondria by upregulating cellular miRNA-4331, resulting in the opening of the mitochondrial permeability transition pore (mPTP) and subsequently to mitochondrial permeability [67,75]. TGEV also downregulates miRNA-27b, which is responsible for inhibiting apoptosis [118]. Similar to PEDV, the TGEV N protein is cleaved by caspase-6 and -7 during apoptosis [74]. It is controversial whether the N protein of TGEV located in mitochondria induces mitochondrial injury [66,119]. Interestingly, TGEV protein 7 inhibits apoptosis [46]. Host cells have developed strategies to eliminate the damage. For example, miRNA-222 in porcine kidney (PK-15) cells as well as mitophagy and circRNA circEZH2 in IPEC-J2 cells regulate the mitochondrial dysfunction during TGEV infection [66,67,120]. p53 inhibits TGEV replication via IFN signaling and promotes cell cycle arrest at the S and G2/M phases [72,121,122]. In vitro studies demonstrate that TGEV induces apoptosis in ST cells and PK-15 cells but not in intestinal epithelial cells [66,70,73,82,123]. As mentioned previously, TGEV induces autophagy to suppress oxidative stress and apoptosis but benefit viral infection in IPEC-J2 cells [66]. In addition, TGEV facilitates pyroptosis, which is a highly inflammatory form of programmed cell death in IPEC-J2 cells [124].
In vivo study shows that PDCoV induces apoptosis via the p38/MAPK signaling pathway in the small intestine of 7-day-old piglets [80]. In addition, PDCoV induces apoptosis in both LC porcine kidney cells and ST cells but not in IPEC-J2 cells [81,83,125,126]. PDCoV can activate DEGs associated with the apoptosis signaling pathway in human and pig intestinal epithelial cells [127]. SADS-CoV induces caspase-dependent extrinsic and intrinsic apoptosis [84]. At 24 h post inoculation (hpi), SADS-CoV-infected Vero E6 cells increase the expression of DEGs associated with negative regulation of the apoptotic process, implying that SADS-CoV inhibits apoptosis [104]. It has been demonstrated that PHEV leads to apoptosis via a caspase-dependent pathway [87]. There has been no study regarding cellular apoptosis in PRCV infection.

Cellular Morphologic Alterations in Swine CoV Infection
Structural and junctional proteins maintain cellular morphology and tissue structure. In the gastrointestinal tract, cell-cell adhesion among epithelial cells is determined by junctional proteins, including tight junctions (TJs), adherence junctions (AJs), and desmosomes. TJs are especially involved in paracellular permeability and contain occludin, claudins, zonula occludens (ZOs), tricellulin, cingulin, and junctional adhesion molecules (JAMs) [128]. The viral infection damages the intact intestinal epithelium. For instance, the human immunodeficiency virus reduces the expression of TJ proteins in intestinal epithelial cells, resulting in intestinal barrier dysfunction and chronic diarrhea [129]. Here, we discuss the major cellular morphologic changes in swine CoV-infected cells, including alterations in tight junctions and the cytoskeleton and EMT induced by chronic ER stress ( Table 2).
The major component of cellular structural proteins is the cytoskeleton, and cytoskeletal filaments consist of actin filaments (also known as microfilaments), microtubules, and intermediate filaments. Actin and microtubules provide intracellular transport pathways to endogenous cargos, while intermediate filaments are responsible for mechanical stability. Viruses may alter the cellular morphology of infected cells during viral infection, leading to cytoskeletal rearrangement and even collapse [130]. For instance, SARS-CoV-2 modulates cytoskeleton components, including actin, microtubules, and intermediate filaments, in Calu-3 cells [131]. SARS-CoV-2 also regulates DEGs associated with cell junctions and the cytoskeleton in lung cells [132].
The infection of PEDV results in a lower expression of ZO-1 in enterocytes both in vivo and in vitro [64,65] (Table 2). In addition, the RNA expression of TJs, including occludin, claudin-1, claudin-4, claudin-5, ZO-1, and ZO-2, reduces in both PEDV-infected 7-day-old piglets and IPEC-J2 cells [133]. These findings suggest that PEDV disrupts the integrity of tight junctions. In the cytoplasm of infected cells, PEDV uses microtubule proteins, including dynein and kinesin-1, for viral transportation [134,135]. In Vero cells, PEDV disrupts the protein levels of the GTPase signaling pathway related to cytoskeletal changes and the protein levels of TJs and AJs [59]. In ST cells, PEDV regulates miRNAs and mRNAs associated with focal adhesion, endocytosis, and regulation of cytoskeletal activity [53].
In IPEC-J2 cells, TGEV reduces the protein levels of E-cadherin, occludin, and ZO-1, indicating that TGEV impairs the integrity of the epithelial barrier [65]. TGEV reorganizes microfilaments with an accompanying cell membrane rearrangement in IPEC-J2 cells [65]. TGEV binds to epithelial growth factor receptor (EGFR) and subsequently activates F-actin polymerization and reorganization, leading to F-actin gathering at the cell membrane [136]. In ST cells, which are mesenchymal in origin, TGEV upregulates the microfilament-associated proteins beta-actin and microtubule-associated alpha-tubulin and beta-tubulin to facilitate viral transport [77] but reduces the expression of actin-associated proteins, including filamin-A, filamin-B, microtubule-associated protein 4, and actin-related protein 2/3, suggesting cytoskeletal disruption [78]. In PDCoV infection, epithelial cells in the jejunum and ileum decrease the expression of ZO-1 with no effect on claudin-1 and occludin [80]. The N protein of PDCoV also enhances the protein expression of ezrin, which is a cytoskeletal protein [39].
It has been demonstrated that PHEV leads to rapid actin rearrangement, implying that the cytoskeleton is associated with viral endocytosis [89]. More specifically, PHEV induces cytoskeletal rearrangement by binding to integrin α5β1 and activating the α5β1-FAK signaling pathway in N2a cells and mice [88,90]. In addition, PHEV relies on microtubules and intermediate filaments of infected cells to propagate within and among nerve cells [137]. To date, no study has focused on the cellular morphology in SADS-CoV or PRCV infection.
A phenotype switching by which epithelial cells lose polarity but gain migratory and invasive properties is known as epithelial-mesenchymal transition (EMT). EMT is critical in embryo development, wound healing, pathological fibrosis, and tumor progression. During EMT, cells lose E-cadherin, a critical component in adherens junctions, but express mesenchymal markers, such as neural cadherin (N-cadherin) and vimentin. EMT is triggered by a series of transcription factors, including Snail, TWIST, and zinc-finger E-box-binding (ZEB) in intestinal epithelial cells [138]. Notably, proinflammatory cytokines, such as the transforming growth factor β (TGFβ) family and IL-17, facilitate Snail expression [139,140]. TGFβ is produced by stressed cells or inflammatory cells and contributes to tissue repair. In humans, EMT is highly involved in the pathogenesis of inflammatory bowel disease (IBD), which is characterized by diarrhea and persistent chronic inflammation, suggesting the role of EMT in the injured digestive tract [141]. TGFβ facilitates EMT in swine intestinal epithelial cells via the MAPK/ERK pathway [76]. Viral and bacterial infection leads to chronic inflammation and subsequent EMT in enterocytes. For instance, Salmonella enterica serovar Typhimurium facilitates EMT of intestinal cells to enhance its invasion [142]. SARS-CoV-2 induces EMT in alveolar epithelial cells and later fibrosis [143].
Chronic infection with PEDV leads to EMT in enterocytes of weaned piglets with increased protein levels of TGFβ, implying persistent injury caused by PEDV [64]. Additionally, PEDV upregulates DEGs associated with the TGFβ signaling pathway in IPEC-J2 cells [32,144]. Persistent TGEV infection induces EMT in enterocytes and later promotes the infection of Escherichia coli [76]. In addition, TGEV upregulates the production of TGFβ as a potential inducer of EMT [145]. TGEV regulates the expression of vimentin in ST cells [77], and knockdown of vimentin in ST cells impairs TGEV replication, indicating that vimentin is essential in viral replication [146]. It is unclear whether PDCoV induces EMT; however, the virus decreases both mRNA and protein expressions of cytoskeletal proteins, including beta-actin and α-actinin-4 (ACTN4), in PK cells [147]. Additionally, PDCoV affects DEGs associated with the TGFβ signaling pathway in both pig and human epithelial cells [127]. In contrast to enteropathogenic coronaviruses that induce structural damage in intestinal epithelial cells, PHEV mainly affects neurons that do not undergo EMT. To date, no study has focused on EMT in SADS-CoV or PRCV infection.

Conclusions
Swine coronaviruses induce enteric, respiratory, and nervous system diseases in pigs. This review reveals the cellular damage and alterations caused by swine CoVs. Functionally, EMT, alterations in cell morphology, and chronic inflammation (Table 2, Figure 3) prevent infected enterocytes from normally absorbing nutrients and therefore lead to the loss of water, ions, and proteins into the intestinal lumen. All other effects such as ER stress, autophagy, and apoptosis culminate in the degeneration and necrosis of infected cells. Thereby, these injuries provide a molecular foundation for the significant clinical and pathological changes (Table 1) and economic losses observed in swine production. More research is needed to understand swine CoVs given that coronaviruses have the capability for recombination and pandemic outbreaks. It is worth mentioning that limited research has focused on PRCV, which is likely underestimated due to the minimal degree of clinical disease. However, regarding the pandemic threat of SARS-CoV, it may be prudent to focus increased attention on PRCV.


s2fieldsofstudy: Biology Medicine Chemistry

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Edaravone Attenuated Particulate Matter-Induced Lung Inflammation by Inhibiting ROS-NF-κB Signaling Pathway

Background Particulate matter (PM) exposure is related to mitochondria dysfunction and airway inflammation. Antioxidant drug edaravone (EDA) is reported to improve the occurrence and development of oxidative stress-related diseases. At present, there is no data on whether EDA can alleviate lung inflammation caused by PM. Methods The anti-inflammatory effects of EDA were investigated in urban PM-induced human bronchial epithelial cells (HBECs) and C57/BL6J mouse models. In vitro, its effects on the production of intracellular reactive oxygen species (ROS), mitochondrial membrane potential (MMP), and inflammatory cytokines were assessed by DCFH-DA staining, JC-1 assay, and real-time PCR, respectively. In vivo, the oxidant stress in lung tissues was assessed by dihydroethidium (DHE) staining and malondialdehyde (MDA) activity, and inflammatory cytokines in bronchoalveolar lavage fluid (BALF) were assessed by ELISA, respectively. Furthermore, the potential signaling pathways were studied by siRNA transfection and western blot. Results PM increased the expression of inflammatory cytokines and protein, including IL-6, IL-1α, IL-1β, and COX-2, while these alternations were significantly alleviated following EDA treatment in a dose-dependent manner. EDA treatment also alleviated the inflammatory responses in lung tissues of PM-exposed mice. We further showed mitochondrial dysfunction in PM-exposed HBECs and mice, which were reversed by EDA treatment. Moreover, the phosphorylation of NF-κB p65 in PM-exposed HBECs and mice was weakened by EDA. Transfection with NF-κB p65 siRNA further inhibited PM-induced inflammation in HBECs. Conclusion We demonstrated that EDA treatment had a protective role in PM-induced lung inflammation through maintaining mitochondrial balance and regulating the ROS-NF-κB p65 signaling pathway. This provided a new therapeutic method for PM-induced lung inflammation in the future.

Introduction
Ambient particulate matter (PM) exposure is a severe public health problem worldwide, and it is the fourth leading risk factor for global death in 2019 [1]. It was reported that 92% of the world's population were exposed to PM 2.5 levels far exceeding the average PM 2.5 transition level of the World Health Organization's Air Quality Guidelines. Furthermore, PM was reported to induce adverse effects on human health after short-term and long-term exposure. Short-term exposure generally causes acute inflammatory responses in airways and peripheral blood [2], while longterm exposure is actively related to the mortality of cardiovascular diseases, respiratory diseases, and cancer [3][4][5]. The increasing burden of PM exposure makes it urgent to control airway diseases caused by PM exposure. Accumulating epidemiological data have proved that short-term PM exposure contributed to the occurrence and development of airway inflammation and mitochondria dysfunction. However, the specific target of interventions is still unclarified.
Mitochondria are sensitive targets of PM and the primary source of oxidative stress that leads to inflammatory responses. Dysfunction mitochondria display decreased mitochondria membrane potential (MMP) and increased ROS production. Once ROS led to a decrease in MMP and an increase in mitochondrial membrane permeability, mitochondrial proapoptotic factors would be released into the cytoplasm, triggering mitochondrial-dependent apoptosis [6]. Cumulative studies suggested that airway inflammation acted as the product of mitochondrial dysfunction [7][8][9]. Thus, our study attempted to explore an effective therapy to reduce PM-related mitochondrial oxidative damage and protect against lung injury.
Edaravone (3-methyl-1 phenyl-2-pyrazoline-5-one, EDA) is a powerful scavenger of hydroxyl radicals, eliminating the hydroxyl radicals that induce lipid peroxidation [10][11][12]. Emerging research showed that it had antioxidation and antiapoptosis effects and pointed out that EDA had a beneficial effect on diseases caused by redox imbalance in inflammatory diseases [13][14][15][16]. Zhang et al. showed that EDA protected against liver and lung injury by reducing the expression of inflammatory cytokines in animal sepsis models [17]. However, the effect of EDA on PM-induced lung injury has not been studied.
Therefore, the present study for the first time demonstrated that EDA protected PM-induced lung inflammation via regulating the ROS-NF-κB signaling pathway in vivo and in vitro.

Animals and Cell
Culture. Animal handling and experiments were conducted following the policies of the animal care facility of Zhongshan hospital, Fudan University. Male 8-12-week-old C57BL/6 mice were acquired from SLAC Laboratory Animals (Shanghai, China). Human bronchial epithelial cells (HBECs) were purchased from the Chinese Academy of Sciences (Shanghai, China) and cultured in RPMI 1640 (Gibco, Waltham, MA, USA) containing 10% FBS (Gibco) and 50 U/mL penicillin and streptomycin (Gibco).
For in vivo experiments, the acute PM-exposed mouse models were established via intratracheal instillation with 100 μg PM in 30 μL PBS per day for 2 consecutive days, according to our previous studies [18][19][20]. EDA (2, 10, or 20 mg/kg) was intraperitoneally injected 1 h prior to PM stimulation every time. PBS was administered following the same protocol to obtain the control group. For in vitro experiments, HBECs were treated with PM at 300 μg/mL for 24 h, according to our previous studies [21,22]. EDA (300, 400, or 500 μM) were used to treat HBECs 1 h before PM stimulation. The dose of EDA for in vitro and in vivo experiments was identified according to the previously reported studies [11,17,[23][24][25][26][27]. To make our results accurate, the concentration gradient of EDA treatment was selected for our study.

Small
Interfering RNA (siRNA) Transfection. NF-κB p65 siRNA was purchased from GenePharma (Shanghai, China). HBECs were transfected with NF-κB p65 siRNA or control siRNA using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA) at a concentration of 50 nM according to the manufacturer's protocol. After transfection, cells were treated with PM for 24 h. Subsequently, certain genes were analyzed by RT-PCR and western blot.
2.4. Real-Time PCR. RT-PCR analysis was carried out to detect the mRNA expression of COX-2, IL-6, IL-1α, and IL-1β. Total RNA extraction from HBECs was performed with the TRIzol Reagent (Invitrogen). Then, RNA was reverse transcribed and quantified by the 7500 RT-PCR system (Applied Biosystems) using the SYBR Green PCR kit (Takara, Japan). All protocols were used as we previously reported [18]. The primers used in our research are listed in Table 1.

Western Blot.
Western blot analyses were performed as previously described [18]. Briefly, the cells and the right lung upper lobe of mice were harvested and lysed in radioimmunoprecipitation assay (RIPA) buffer containing 1% phenylmethanesulfonyl fluoride (PMSF) and 1% phosphatase inhibitors (Biotool, Houston, TX, USA). Subsequently, the homogenate was centrifuged at 12,000 g for 30 min at 4°C, and the supernatant was collected.
After cell homogenates were boiled, the proteins (30 μg) were separated by SDS-PAGE and transferred to the PVDF membranes. After blocking with western blocking buffer for 1 h at room temperature, membranes were incubated with primary antibody against phospho-NF-κB p65, NF-κB p65, COX-2, GAPDH, or β-actin overnight at 4°C, respectively. Then, the membranes were washed with TBST thrice and incubated with goat anti-rabbit or goat anti-mouse horseradish peroxidase-(HRP-) conjugated secondary antibodies. The targeted proteins were detected by ECL reagents. The intensity of protein bands was quantified by Image J software (v1.8.0).

ROS Measurement.
The DCFH-DA fluorescent dye probe was used to measure intracellular ROS production. One day after seeding, cells were pretreated with EDA (300, 400, or 500 μM) for 1 h, then treated with 300 μg/mL PM for another 1 h. Then, cells were washed with PBS and incubated with 10 μM DCFH-DA at 37°C for 15 min in the dark. Cells were washed with PBS twice, and images were obtained using the fluorescence microscope (Olympus, Tokyo, Japan) equipped with a digital camera. For in vivo studies, fresh lung tissues were embedded in OCT, sectioned, and stained with DHE to detect ROS, as described previously [18]. DHE entered cells and was oxidized by superoxide to emit red fluorescence detected by the fluorescence microscope. The value of relative fluorescence intensity was 2 Oxidative Medicine and Cellular Longevity measured in selected areas that contain cells and was analyzed by Image J software (v1.8.0).

JC-1 Assay for Mitochondrial Membrane Potential.
MMP was measured using a mitochondrial-specific dualfluorescence probe, JC-1 (Beyotime). Briefly, HBECs were seeded into 12-well plates, treated with or without EDA (300, 400, or 500 μM) for 1 h, and then treated with 300 μg/mL PM for another 24 h. Next, cells were washed with PBS and incubated with 10 μg/mL JC-1 at 37°C in the dark for 30 min. The fluorescence was measured by a microscope. The red fluorescence represents the JC-1 monomers, while the green fluorescence represents JC-1 aggregates. The ratio of red fluorescence to green fluorescence was calculated to indicate the level of MMP.
2.8. Malondialdehyde (MDA) Activity. The right lung middle lobe and right lung lower lobe of mice were harvested. The tissue samples were homogenized and sonicated in 300 μL RIPA buffer on ice. Then, tissue lysates were centrifuged at 12,000 g for 15 min at 4°C, and the supernatant was collected. The proteins were diluted to the appropriate concentration and subjected to the MDA assay as described in the Lipid Peroxidation MDA assay kit (Beyotime). The MDA levels were detected by Multi-Mode Microplate Readers (BioTek, Santa Barbara, CA, USA) at 532 nm.

H&E Staining and Immunohistochemistry (IHC).
Mice from different groups were intraperitoneally injected with avertin (Sigma-Aldrich) for euthanasia at the dose of 25 mg/kg body weight, and the left lung lobe of mice was   Oxidative Medicine and Cellular Longevity harvested and fixed in 4% paraformaldehyde. Then, the left lung was sliced and stained with hematoxylin and eosin (H&E) staining according to the manufacturer's instructions [18]. Pathologic changes were imaged and scored as reported previously [28].
Paraffin-embedded left lung tissue sections were stained by IHC. The slices were incubated with 3% H 2 O 2 and then were incubated with a primary antibody against COX-2 at 4°C for 12 h. The second antibody labeled with horseradish peroxidase was incubated at 37°C for 30 min, and the immunohistochemical reaction was observed according to the manufacturer's instructions with 3,3 ′ -diaminobenzidine (DAB) as a chromogenic agent [28]. IHC staining was evaluated by ImageJ software (v1.8.0) according to the MOD value.

Bronchoalveolar Lavage Fluid (BALF) Collection and
Inflammatory Cell Counts. Mice were intraperitoneally injected with avertin for euthanasia at the dose of 25 mg/kg body weight. After euthanasia, the chest of each mouse was opened to collect the BALF. The trachea and the whole lung were cannulated and perfused with 1 mL normal saline. A three-in and three-out pattern of main bronchial instillation was adopted, and the BALF was collected with a high recovery. The BALF was centrifuged at 800 g for 5 min at room temperature. The supernatant was collected and stored at -80°C for further analysis. Cell pellets were resuspended with 0.5 mL of PBS, and the total cell number was counted. Then, 100 μL of the resuspended cells was spun to the slide, airdried, and then fixed with 4% paraformaldehyde overnight. Cells were stained with H&E, and the number of macrophages and neutrophils in 200 cells was counted. The data were shown as 10 5 /mL BALF.
2.11. Enzyme-Linked Immunosorbent Assay (ELISA). The protein expression levels of IL-6, IL-1α, and IL-1β in the BALF were measured using ELISA kits (4A Biotech, Beijing, China) according to the manufacturer's instructions [18]. Values were expressed as pg/mL and deduced from standard curves of recombinant cytokines.
2.12. Statistical Analyses. The GraphPad Prism 5 software (GraphPad, Inc., La Jolla, CA, USA) was used to analyze all data. The significance of differences between control and experimental values was assessed using the unpaired t-test or one-way analysis of variance (ANOVA). P <   Oxidative Medicine and Cellular Longevity 0:05 was considered statistically significant. All values were expressed as the mean ± standard error of the mean ðSEMÞ.

EDA Attenuated PM-Induced Inflammation in HBECs.
To investigate the anti-inflammatory effect of EDA on HBECs, the cells were treated with 300, 400, or 500 μM EDA for 1 h, respectively, and then stimulated with 300 μg/ mL PM for an additional 24 h. The mRNA levels of inflammatory cytokines, including IL-6, IL-1α, and IL-1β, were significantly increased in HBECs with PM stimulation, and the increasing level of inflammatory cytokines was significantly decreased by EDA treatment in a dose-dependent manner in HBECs with PM stimulation (Figure 1(a)). COX-2 was induced by several inflammatory stimuli, and its expression was increased significantly by PM exposure in this study, as we previously reported [18]. EDA treatment could significantly decrease the expression of COX-2 in HBECs exposed to PM at the gene and protein levels (Figures 1(b)-1(d)). These results suggested that EDA could inhibit PMinduced inflammation in HBECs. . These results suggested that EDA attenuated oxidative stress and treated mitochondrial imbalance in HBECs exposed to PM.

EDA Inhibited PM-Induced Inflammation In Vivo.
To clarify the anti-inflammation and antioxidative effect of EDA on PM-induced mice, mice were treated with EDA (2, 10, or 20 mg/kg) before PM exposure every time. Our results showed that EDA could dose-dependently attenuate the infiltration of inflammatory cells in lung tissues of mice exposed to PM (Figures 3(a) and 3(b)). Furthermore, the increasing number of the total cell, neutrophils, and macrophages in BALF in the PM group was significantly inhibited by EDA pretreatment in a dose-dependent manner (Figure 3(c)). Besides, we found that alone EDA treatment

Oxidative Medicine and Cellular Longevity
in different concentrations has no toxic effect on the lung tissues and on blood cell numbers ( Figure S1).
ELISA showed that EDA could attenuate PM-induced production of inflammatory cytokines IL-6, IL-1α, and IL-1β (Figure 4(a)). Meanwhile, the expression of COX-2 was analyzed using IHC, and we found that EDA significantly decreased PM-induced expression of COX-2 in bronchial epithelium in a dose-dependent manner (Figures 4(b) and  4(c)). Similarly, we tested the expression of COX-2 in lung tissues using western blot and showed that EDA treatment inhibited the expression of COX-2 in lung tissues of mice exposed to PM (Figures 4(d) and 4(e)). Besides, we found alone EDA treatment had no effect on inflammatory and COX-2 expression in normal lung tissues ( Figure S2). These results indicated that EDA could significantly inhibit PM-induced lung inflammation in vivo.

EDA Decreased PM-Induced Oxidative Stress In Vivo.
The ROS level in lung tissues was detected with DHE staining and MDA activity. The ROS level in lung tissues of the PM-induced mouse model was significantly increased, and EDA treatment significantly reduced the PM-induced ROS generation in a dose-dependent manner (Figures 5(a) and  5(b)). Furthermore, the levels of MDA in lung tissues were also significantly increased in the PM group compared with those in the control group. EDA dose-dependent treatment significantly attenuated the levels of MDA induced by PM exposure (Figure 5(c)). These results showed that the levels of ROS in lung tissues were inhibited by EDA treatment in PM-exposed mice.  Oxidative Medicine and Cellular Longevity effect of EDA on the NF-κB p65 pathway in PM-induced inflammatory responses, western blot was used the test the activation of the NF-κB p65 pathway. We found that pretreatment with EDA blocked PM-induced activation of the NF-κB p65 pathway in HBECs (Figures 6(a) and 6(b)). We also found that EDA treatment significantly decreased the expression of phospho-NF-κB p65 in PM-induced lung inflammation in a dose-dependent manner (Figures 6(c) and 6(d)). Besides, we performed a knockdown of NF-κB p65 by transfection with NF-κB p65 siRNA in HBECs to further clarify the key role of the NF-κB p65 signaling pathway in PM-induced inflammation. The efficiency of NF-κB p65 siRNA was examined by RT-PCR and western blot. We found a decrease in the expression of NF-κB p65 in HBECs after transfection with NF-κB p65 siRNA with or without PM exposure (Figures 6(e)-6(g)). Furthermore, we found that knockdown of NF-κB p65 significantly attenuated the production of inflammatory cytokines, including IL-6, IL-1α, and IL-1β in PM-exposed HBECs (Figure 6(h)). These results suggested that NF-κB p65 signaling pathway activation played a vital role in PMinduced inflammation and EDA treatment could inhibit the activation of the NF-κB p65 signaling pathway to alleviate PM-induced inflammation.

Discussion
Inflammation is the primary biological mechanism of PM-induced lung damage and is responsible for the PMinduced development and exacerbation of chronic respiratory diseases. In this study, we showed that PM exposure triggered mitochondrial damage with the rapid increase in ROS and loss of MMP and thus promoted inflammatory cytokines and COX-2 expression in HBECs. EDA as the antioxidative drug decreased ROS production, reversed the MMP, and further inhibited the activation of the NF-κB p65 signaling pathway in PM-induced HBECs and lung tissues (Figure 7). To our knowledge, this is the first study to demonstrate the protective effect of EDA on PM-induced lung inflammation. EDA is clinically approved for treating stroke and amyotrophic lateral sclerosis (ALS) in previous researches by removing hydroxyl radicals. It can also modulate inflammatory processes, matrix metalloproteinase levels, nitric oxide production, apoptotic cell death, and necrotic cell death [11,16,17]. Tajima et al. found that EDA prevented lung injury and attenuated inflammatory cell activation and the release of inflammatory cytokines (IL-6 and TNF-α) in the BALF of the LPS-induced ALI mouse model [29]. It was also reported that EDA attenuated LPS-mediated inflammatory response in astrocytes [30]. Thus, EDA might be a powerful drug for inhibiting inflammatory responses. However, the protective effects of EDA on PM-induced inflammatory responses in the lung were unknown so far. In this study, we used PM-induced HBECs and mice to investigate the anti-inflammatory role of EDA. Our results provided direct evidence that EDA protected against PM-induced inflammation in HBECs and lung tissues of mice in a dose-dependent manner.
The signs of mitochondrial metabolic dysfunction included the increased ROS and loss of the membrane potential difference between the inner and outer membranes, which were also the hallmark of apoptotic mitochondrial damage [31]. Mitochondria constitute a significant source of ROS, affecting inflammatory response processes [32]. Previous studies showed that oxidative stress participated in regulating PM-induced inflammatory response, cell apoptosis, and even lung injury [33,34]. Ning et al. found that the expression of antioxidant enzymes, superoxide dismutase 2 (SOD2), SOD3, and peroxiredoxin 4 (PRDX4) was decreased in PM-exposed lung tissues of mice [35]. Similar to these previous studies, we detected that PM exposure decreased MMP and further promoted ROS production in HBECs. EDA exhibits beneficial effects on free radical scav-enging and maintaining the stability of MMP. Li et al. found that EDA treatment could increase ATP and mitochondrial membrane potential levels by augmenting the expression of Nrf2 and the target genes in excessive evaporation-induced dry eyes [36]. Reyes et al. found that EDA inhibited ischemia-reperfusion injury-induced pulmonary dysfunction by suppressing MDA levels and the expression of inflammatory cytokines [37]. Similarly, we firstly found that EDA could inhibit PM-induced mitochondrial imbalance and ROS production in vitro and in vivo. Elimination of oxidative stress may be a strategy to prevent PM-induced inflammation.
The NF-κB pathway plays a crucial role in inflammatory responses by regulating the transcription of inflammatory cytokine genes [38]. Hassanein et al. demonstrated that EDA prevented cyclophosphamide-induced hemorrhagic cystitis and increased MDA by suppressing the NF-κB signaling pathway in rats [39]. We also reported that PM exposure induced the activation of the NF-κB pathway and increased the production of IL-6, IL-8, IL-1β, and COX-2 in HBECs [18]. In this study, we further demonstrated that the NF-κB pathway was also significantly activated in PM-induced lung tissues of mice. Knockdown of NF-κB p65 significantly inhibited the expression of inflammatory cytokines induced by PM exposure in HBECs. Besides, the dose of PM exposure and EDA treatment in our studies was identified according to the previously reported studies [11,17,18,[23][24][25][26][27]. Based on the human exposure dose equivalent to the mouse-aspirated dose covert algorithm [40], we found that 100 μg PM 2.5 exposure for mice via intratracheal instillation was equivalent to 141 μg/ m 3 PM 2.5 exposure for humans in 24 hours. According to the World Health Organization (WHO) air quality guidelines, the recommended short-term (24-hour) AQG level of interim target-1 of PM 2.5 is 75 μg/m 3 . Thus, the dose of PM exposure for mice in our study could contribute to lung damage. To make our results more accurate, we selected the concentration gradient of EDA for our study. EDA has been widely used in clinical treatment of acute cerebral infarction, and the recommended dose of EDA was 30 mg twice a day according to the drug instruction. According to the drug dose convert algorithm between humans and mice based on the body surface area [41], the concentration of EDA in our study was equivalent to 0.163, 0.813, and 1.626 mg/kg for humans. Thus, the concentration of EDA for the clinical treatment was included in our concentration range in this study. Furthermore, we demonstrated that alone EDA treatment with different concentrations had no toxic effect in our study.

Conclusion
Taken together, we firstly found that EDA inhibited the expression of IL-6, IL-1α, IL-1β, and COX-2 production in HBECs and mice exposed to PM. Meanwhile, EDA attenuated PM-induced mitochondrial dysfunction, ROS overproduction, and activation of the NF-κB signaling pathway. We demonstrated that EDA could significantly alleviate PMinduced lung inflammation by inhibiting the ROS-NF-κB p65 signaling pathway in vitro and in vivo. These data provided evidence that EDA would be a beneficial therapeutic choice in preventing and treating the harmful effects of PM exposure in the future.

Data Availability
All supporting the findings of this report are included in this article. Source raw data for all quantitations is fully available upon request.

Conflicts of Interest
The authors declare that there is no conflict of interest regarding the publication of this paper.

Authors' Contributions
Yingying Zeng, Guiping Zhu, and Mengchan Zhu contributed equally to this work.  Oxidative Medicine and Cellular Longevity


Identification of the most common BRCA alterations through analysis of germline mutation databases: Is droplet digital PCR an additional strategy for the assessment of such alterations in breast and ovarian cancer families?

Breast and ovarian cancer represent two of the most common tumor types in females worldwide. Over the years, several non-modifiable and modifiable risk factors have been associated with the onset and progression of these tumors, including age, reproductive factors, ethnicity, socioeconomic status and lifestyle factors, as well as family history and genetic factors. Of note, BRCA1 and BRCA2 are two tumor suppressor genes with a key role in DNA repair processes, whose mutations may induce genomic instability and increase the risk of cancer development. Specifically, females with a family history of breast or ovarian cancer harboring BRCA1/2 germline mutations have a 60-70% increased risk of developing breast cancer and a 15-40% increased risk for ovarian cancer. Different databases have collected the most frequent germline mutations affecting BRCA1/2. Through the analysis of such databases, it is possible to identify frequent hotspot mutations that may be analyzed with next-generation sequencing (NGS) and novel innovative strategies. In this context, NGS remains the gold standard method for the assessment of BRCA1/2 mutations, while novel techniques, including droplet digital PCR (ddPCR), may improve the sensitivity to identify such mutations in the hereditary forms of breast and ovarian cancer. On these bases, the present study aimed to provide an update of the current knowledge on the frequency of BRCA1/2 mutations and cancer susceptibility, focusing on the diagnostic potential of the most recent methods, such as ddPCR.

Introduction
Breast and ovarian cancer are two of the most common malignancies affecting the female population both in industrialized and developing countries. According to GLOBOCAN 2020, breast cancer is the most frequently diagnosed tumor among females with 2,261,419 new cases (24.5%) and the first leading cause of cancer-related death with 684,996 deaths (15.5%). On the other hand, ovarian cancer represents the eighth most common cancer for incidence and mortality in females, accounting for 313,959 newly diagnosed cases (3,4%) and 207,252 deaths (4.7%) (1).
Over the years, several risk factors have been associated with the onset and progression of both breast and ovarian cancer (Fig. 1). As widely reported in the literature, more than half of all cases diagnosed are females aged >50 years, indicating that age is one of the major non-modifiable risk factors (2,3). Similarly, reproductive factors, such as age at menarche and menopause (before 11 and after 55 years of age, respectively), nulliparity and age at first full-term pregnancy (>35 years), are well-established risk factors for both breast and ovarian cancer (4,5). Furthermore, post-menopausal hormone therapies, based on the administration of estrogens plus progestin, significantly increase the risk of cancer development (6,7). Of note, the use of oral contraceptives for birth control has only been described as a risk factor for breast cancer, while oral contraceptive pills represent a protective factor for ovarian cancer, reducing the risk by at least 50% when used for 10 years or more (8)(9)(10). Other risk factors for both of these female cancer types include ethnicity, tobacco smoking, alcohol consumption, low physical activity, high-fat diet, obesity and socioeconomic status (11)(12)(13)(14)(15)(16). Several studies have demonstrated that environmental, lifestyle and epigenetic factors are associated with the development of both breast and ovarian cancer (17)(18)(19)(20).
Besides the aforementioned modifiable and non-modifiable risk factors, a family history of breast and/or ovarian cancer, as well as genetic mutations, may have a key role in increasing cancer susceptibility. Of note, a growing body of evidence suggests that the risk of developing these female cancers is significantly increased in females having a first-degree relative affected by breast cancer or ovarian cancer or when the affected relative was under 50 years of age (21)(22)(23)(24). Of note, over the years, several genetic mutations have been reported to be highly associated with an increased risk of both breast and ovarian cancer. Among these, BReast CAncer 1 (BRCA1) and BRCA2 are two tumor suppressor genes with high penetrance, which are involved in the activation of DNA repair processes and cell-cycle checkpoints in response to DNA damage (25,26). Functional deficiencies due to BRCA1/2 mutations induce genome instability, cell-cycle dysregulation and accumulation of other mutations (27,28). In this field, it has been widely demonstrated that BRCA1/2 mutations increase the lifetime risk to develop breast or ovarian cancer. Specifically, 5-10% of patients with breast cancer and 25% of ovarian cancer cases are due to an inherited genetic mutation affecting BRCA1 or BRCA2 (29,30). Furthermore, healthy individuals harboring germline mutations of BRCA1/2 had a 60-70% increased risk to develop breast cancer and a 15-40% increased risk for ovarian cancer (31,32). Therefore, the assessment of cancer-related risk factors, particularly the identification of BRCA1 and BRCA2 gene mutations, is crucial for the clinical management of females at a high risk of developing breast or ovarian cancer, which includes annual screening, chemoprevention and preventive surgery (33,34).
Although the impairment of DNA repair mechanisms due to BRCA mutations is associated with an increased risk of breast and ovarian cancer, patients developing these tumors benefit from therapies further affecting the DNA repair machinery aimed at killing cancer cells through the accumulation of several DNA alterations resulting in tumor cell death (35,36). Among these therapies, the use of poly [ADP-ribose] polymerase (PARP) inhibitors directed at PARP proteins involved in DNA repair mechanisms proved to be highly efficient in both ovarian and breast cancer (37,38).
The precise molecular characterization of both breast and ovarian tumors is essential to correctly classify cancer lesions and predict the prognosis of patients. With regard to breast cancer, the presence of hormone receptors (estrogen receptor and progesterone receptor), membrane receptors (epidermal growth factor receptor) and other molecular markers, including BRCA1/2 mutations, are used to classify breast cancer into different molecular subtypes (39). Besides its molecular classification, breast cancer may be divided according to histological features, e.g. ductal carcinoma, lobular carcinoma, mucinous carcinoma or spindle cell carcinoma (40,41).
As mentioned above, the precise identification of molecular markers such as BRCA1/2 mutations is essential to predict the prognosis of patients. In this context, both BRCA1 and BRCA2 mutations are associated with a higher aggressiveness of both breast and ovarian cancer (42). However, due to the development of novel targeted therapies using high-effective PARP inhibitors (olaparib, niraparib, recuparib and veliparib) for the treatment of tumors with BRCA mutations, the presence of these mutations in ovarian cancer is associated with a favorable prognosis (43). Despite the prognostic importance of BRCA1/2 mutations, the identification of other proteins or genetic and epigenetic factors is essential to predict the efficacy of treatments and the survival of patients (44).
The BRCA1 gene is located on the long arm of chromosome 17 (17q21) and it is composed of 24 exons (45). BRCA1 encodes for a multi-functional protein of 1,863 amino acids, which consists of an amino (N)-terminal RING domain, a carboxyl (C)-terminus, also known as the BRCT domain, and coding regions of exons 11-13 ( Fig. 2) (46,47). These domains have a crucial role in the interaction between BRCA1 and several partner proteins. The RING domain (amino acids 1-109) is a highly conserved domain encoded by exons 2-7, which is characterized by a RING finger motif involved in the ubiquitination pathway. Of note, it heterodimerizes with BRCA1 associated RING domain 1 (BARD1) to form a dimeric RING ubiquitin-ligase (E3) (48). The BRCT domain is encoded by exons 16-24 and spans from amino acids 1,650-1,863, including two tandem repeats (~100 amino acids) linked by 22 amino acids. This domain binds to the phosphorylated serine-proline-x-phenylalanine motifs of different partner proteins, such as BTB domain and CNC homolog 1 (BACH1), BRCA1 interacting helicase 1, BRCA1 A complex subunit and C-terminal binding protein 1, to form functional macromolecular complexes that allow selecting the substrate for BRCA1-BARD1 activity (49)(50)(51)(52). Compared to other domains, exons 11-13 cover a large part of the BRCA1 protein. Of note, exon 11 comprises two nuclear localization sequences (NLS) (amino acids 501-507 and 607-614), which facilitate the nuclear import process of BRCA1 interacting with importin α (53).
As widely described in the literature, BRCA1 may be considered a tumor suppressor gene whose derived protein is involved in several molecular pathways both in the nucleus and cytoplasm, including DNA double-strand break (DSB) repair, cell-cycle checkpoints, genome stability, transcription regulation, apoptosis, chromosomal segregation, mitochondrial genome repair, cytoskeletal rearrangements and centrosome regulation ( Fig. 2) (54)(55)(56)(57).
It has been reported that DNA DSBs activate several kinases, such as ATM, ATM-related kinase, checkpoint kinase 1 (Chk1) and Chk2, which phosphorylate BRCA1 (58,59). The hyperphosphorylated BRCA1 then interacts with several protein complexes that repair DSBs via homologous recombination repair (HRR) and the activation of cell-cycle checkpoints. Of note, BRCA1 is involved in HRR through the interaction with the RAD50-MRE11-NBS1 complex, as well as partner and localizer of BRCA2 (PALB2) and RAD51 DNA repair proteins (60)(61)(62). Regarding cell-cycle checkpoints, other BRCA1 complexes have been described. Specifically, G2/M checkpoint signaling is activated by BRCA1-receptor-associated protein 80, while the BRCA1-BACH1 complex is required during the S-phase (63,64). BRCA1 also regulates gene expression at the transcriptional level, interacting with RNA polymerase II and several transcription factors, including c-Myc, p53, histone deacetylase 1 and 2, signal transducer and activator of transcription 1 and zinc finger and BRCA1-interacting protein with KRAB domain-1, as well as the SWItch/sucrose non-fermentable complex (65)(66)(67)(68)(69)(70). Of note, the ubiquitin-ligase activity of the BRCA1-BARD1 complex has a critical role in centrosome regulation. In particular, BRCA1 and BARD1 bind to Obg-Like ATPase 1, favoring the maintenance of centrosome numbers at S-and G2/M-phases (71). Furthermore, BRCA1 has apoptotic properties due to its nuclear export and the activation of the p53-independent growth arrest and DNA damage-inducible 45 regulatory sequences (72).
BRCA2 was described for the first time in 1995 by Wooster et al (73) analyzing breast cancer families. The BRCA2 gene is located on the long arm of chromosome 13 (13q12.3) and it is composed of 27 exons that encode for a protein of 3,418 amino acids. BRCA2 consists of an N-terminal domain, a middle region and a C-terminal domain, which mediate its interaction with different partner proteins (Fig. 3). Although the structures of BRCA1 and BRCA2 exhibit certain similarities, there is no sequence homology (74,75). Of note, the N-terminal domain, encoded by exons 1-10, spans from amino acids 1-636 and contains a transcription activation domain (TAD) essential for PALB2 binding (21-39 amino acids) (76). The central segment is encoded by exon 11 (637-2280 amino acids) and covers the major portion of the BRCA2 protein. This evolutionarily conserved region is characterized by eight repeats of ~35-40 amino acids, also known as BRC repeats, which represent the primary interaction sites for the recombination enzyme RAD51 (77). Regarding the C-terminal domain (exons 12-27), it spans from amino acids 2,281-3,418 and includes the DNA-binding domain composed of a helical domain (amino acids 2,482-2,668) and three oligonucleotide-binding folds (amino acids 2,670-3,184).
Similar to BRCA1, the BRCA2 gene is considered a caretaker of genome stability that has a key role in several biological pathways. Of note, it has been reported that BRCA2 interacts with different partner proteins for the formation of macromolecular complexes performing distinct cellular functions, such as DNA DSBs repair by HRR, DNA replication fork stabilization, transcription regulation and cell cycle checkpoint regulation ( Fig. 3) (79)(80)(81)(82).
For instance, the interaction between BRCA2 and RAD51 is implicated in the repair of DNA damage by the HRR pathway. Of note, BRC repeats, as well as the C-terminal domain of BRCA2, regulate the assembly of RAD51 into a nucleoprotein filament, promoting strand invasion and the search for homologous DNA (83,84). Other partner proteins interact with BRCA2 forming macromolecular complexes that have a crucial role in DNA DSB repair and maintenance of genome stability, including BARD1, PDS5 cohesin-associated factor B and SEM1 26S proteasome subunit (85)(86)(87). BRCA2 also promotes the stabilization of stalled DNA replication forks. Specifically, BRCA2 directly interacts with PALB2 through TAD of the N-terminal domain to sustain the recruitment of polymerase η at blocked replication forks (88). Furthermore, Fanconi anemia complementation group D2 and biorientation of chromosomes in cell division 1-like proteins have been described to interact with BRCA2 and promote stalled fork protection (89,90). Of note, BRCA2 may act as a transcriptional co-regulator forming a functional complex with mothers against decapentaplegic homolog 3 (SMAD3). BRCA2 induces SMAD3-dependent transcriptional activation of plasminogen activator inhibitor 1, while SMAD3 increases the transcriptional activity of BRCA2, indicating a synergistic activity of these two proteins (91). Furthermore, it has been reported that the binding between BRCA2 exon 3 and the nuclear protein EMSY (BRCA2-interacting transcriptional repressor) is involved in chromatin remodeling and transcription regulation (92). Finally, although the direct role of BRCA2 in cell-cycle checkpoints remains to be fully clarified, the interaction between BRCA2 and BRCA2-associated factor 35 may be responsible for G2/M checkpoint modulation (93).
On these bases, the present study aimed to provide an update of the current knowledge on BRCA1 and BRCA2 mutations and cancer susceptibility, focusing on their physiological functions, mutation frequency and clinical impact, as well as the available genetic tests and new potential technologies for the detection of BRCA1/2 mutations.

Materials and methods
Identification of the most common BRCA1/2 genetic variants and their clinical significance. The analysis of BRCA1 and BRCA2 mutations was performed using the Breast Cancer Information Core (BIC) (https://research.nhgri.nih. gov/bic/, accessed on 3 February 2022), BRCA Exchange (https://brcaexchange.org/, accessed on 15 February 2022) and ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/, accessed on 7 February 2022) public databases. Specifically, a total of 15,311 BRCA1 and 14,914 BRCA2 mutations were registered in the BIC database. Among these, the top 10 most common BRCA1 and BRCA2 genetic variants were selected for evaluation of their clinical significance. In this regard, the BIC designation of BRCA1/2 mutations was matched with data reported in the BRCA Exchange and ClinVar databases in order to classify them into variants that are benign, likely benign, pathogenetic or of uncertain significance.

Identification of BRCA1 and BRCA2 founder mutations.
A literature search of studies published from 1995 until November 2021 was conducted using the PubMed public database (https://pubmed.ncbi.nlm.nih.gov/) in order to investigate interethnic mutation frequencies.
The key words 'breast cancer', 'ovarian cancer', 'BRCA1 mutations', 'BRCA2 mutations', 'BRCA founder mutations', 'BRCA germline mutations' or 'BRCA somatic mutations' were used to identify potentially relevant studies. In addition, the references contained in the most relevant studies were manually retrieved to find relevant articles not retrieved by PubMed exploration. Of note, the mutation frequency analysis was performed focusing on specific regions and ethnic groups, including Ashkenazi Jews, as well as populations from China, Denmark, Finland, France, Germany, Italy, Japan, Korea, Norway, Philippines, Poland, Russia and Sweden. In cases of overlapping data with the other published articles, the latest published and/or the larger sample size study was selected. Articles with ambiguous annotation of data, published in non-English or in Chinese language and duplicate publications were not included.

BRCA1/2 mutation frequency and cancer susceptibility.
Both endogenous and external DNA-damaging agents, including mutagens and radiation, as well as spontaneously occurring mutations, constantly threaten the integrity of the genome. Of note, DSBs represent the most damaging lesions of DNA, which may lead to chromosomal aberrations and mutations, increasing the risk of developing genetic disorders strictly related to cancer susceptibility (94). In this field, it has been widely reported that BRCA1 and BRCA2 tumor suppressor genes are involved in the repair of DNA DSBs by HRR. Specifically, BRCA1 promotes end resection and recruits PALB2, inducing chromatin localization of BRCA2. On the other hand, BRCA2 facilitates the recruitment of RAD51 recombinase, which inhibits the annealing of complementary ssDNA into the deleterious single strand (95). However, BRCA1 and BRCA2 mutations may increase the susceptibility to several tumor types, particularly breast and ovarian cancer (96,97). Indeed, BRCA1/2 loss of functions leads to genomic instability, which may result in the oncogenic transformation of normal cells into tumor-initiating cells (42). BRCA1/2 mutations may be classified into germline and somatic mutations. Germline mutations are inherited in an autosomal dominant manner, while somatic mutations may arise de novo in tumor tissues due to a combination of genetic and environmental factors (98). Regarding BRCA1/2 germline mutations, loss of heterozygosity results in a non-functional protein that leads to Hereditary Breast and Ovarian Cancer (HBOC) syndrome, which is associated with increased susceptibility for these female tumors (99). Furthermore, inherited bi-allelic mutations of both BRCA1 and BRCA2 may cause congenital syndromes that are strictly associated with developmental anomalies, chromosomal fragility and increased cancer risk (100). In particular, the risk of breast cancer for females with a pathogenic BRCA1 or BRCA2 germline variant is 55-72% and 45-69%, respectively. Similarly, the risk for ovarian cancer is 39-44% for females with a BRCA1 germline variant and 11-17% for those with a BRCA2 germline variant (101). On the other hand, it has been reported that BRCA somatic mutations account for 15-30% of all BRCA1 and BRCA2 mutations. In addition, these non-inherited mutations are only present in 3% of all breast cancer cases (102).
Over the years, a large number of BRCA1/2 mutations have been described, and several of them are reliably known to increase cancer susceptibility (103). As reported in ClinVar, thousands of pathogenic or likely pathogenic BRCA1 and BRCA2 variants have been identified (>2,900 and >3,500, respectively) (https://www.ncbi.nlm.nih.gov/clinvar/, accessed 7 February 2022). The pathogenic or likely pathogenic mutations account for 80% of all mutations and result in a premature termination codon and truncated protein. Furthermore, missense mutations encoding a stable mutant protein account for 10% of all missense variants. Of note, frameshift mutations are more common in BRCA1, whereas missense mutations are more frequent in BRCA2 (104).
In the BIC database, a total of 15,311 BRCA1 mutations were registered, of which 6,133 are frameshift mutations, 4,577 are missense mutations and 1,421 are nonsense mutations. Regarding BRCA2, 14,914 mutations were registered (3,567 frameshift, 7,156 missense and 1,040 nonsense mutations). Of note, the mutation with the highest number of entries for BRCA1 was 185delAG, followed by 5382insC, whereas the most frequent mutation for BRCA2 was 6174delT (https://research.nhgri.nih.gov/bic/, accessed on 3 February 2022). Table I summarizes the most common BRCA1 and BRCA2 mutations registered in the BIC database.

BRCA1/2 founder mutations among the worldwide population.
In the last decades, an increasing number of studies have reported that certain BRCA1/2 mutations, also known as founder mutations, were more frequent in specific regions and ethnic groups. For instance, 185delAG, 5382insC and 6174delT mutations have been detected in Ashkenazi Jews, which accounted for 99% of the pathogenic variants identified in this population. Of note, the 5382insC founder mutation has also been identified in other countries, such as Poland and Russia, accounting for 94 and 60% of BRCA1 mutations, respectively. Other BRCA1 founder mutations have been observed in these countries, including C61G and 4154delA among the Polish population and G1706A in Russians (105)(106)(107)(108).
As for Central European regions, it has been reported that 3600del11 and G1710X were the most frequently detected BRCA1 mutations in the French population (115). On the other hand, numerous founder mutations were detected among Germans, such as G1706A, C61G, 2804delAA and IVS12-1643del3835 for BRCA1 and 5579insA and 6503delTT for BRCA2 (116). Of note, the 5083del19 mutation exhibited a high rate in Italian families from Calabria, while 8765delAG was observed in certain Sardinian families (117)(118)(119).
Finally, different BRCA1/2 founder mutations have been also discovered in Asian populations. Of note, L63X, Q934X and 5802delAATT have been identified in Japanese, while the most common mutations among Koreans were 1041del3insT for BRCA1 and 7708C>T for BRCA2 (120)(121)(122)(123). In addition, 1100delAT, 3337C>T and 9325insA were more frequently detected among Chinese, whereas 5454delC and 4859delA were the most common BRCA1/2 founder mutations in the Philippine population (124,125). The distribution of BRCA1/2 founder mutations is summarized in Tables II and III.

Discussion
To date, thousands of mutations have been identified in the BRCA1 and BRCA2 genes. Most of the described mutations are caused by small insertions or deletions, large genomic rearrangements (LGRs), as well as nonsense mutations and splice variants (126). As previously described, certain mutations have been more frequently detected in specific geographical areas and ethnicities (127). Furthermore, it has been reported that each family group may carry a specific mutation that may be considered unique (128). Functional deficiencies due to these pathogenic mutations increase the lifetime risk to develop both breast and ovarian cancer. Of note, the most common cause of these female tumors is HBOC syndrome. Females harboring BRCA1/2 germline mutations have a higher risk of cancer development compared to other subjects (129,130). Therefore, the usage of reliable genetic tests for the assessment of BRCA1/2 mutations in high-risk females is crucial for the clinical management of patients. Over the years, different platforms have been developed for the detection of BRCA mutations (Fig. 4). Among these, the Sanger method has been widely employed for genomic DNA sequencing. In brief, this method allows division of large genomic DNA into small fragments that are sequenced separately (131,132). Although the Sanger sequencing method is considered a reliable technology with a relatively simple workflow, it has several limits, such as sequencing throughput (a single DNA fragment at a time), time-consuming analysis and low cost-effectiveness (133).
Currently, the gold standard genetic test for the identification of BRCA1/2 mutations is next-generation sequencing (NGS). NGS is a high-throughput technology based on synthesis by sequencing millions of DNA fragments at once. Compared to Sanger sequencing, NGS has numerous other advantages, including automated analysis, faster turnaround time and higher sensitivity to detect LGRs and low-frequency variants with deep sequencing (134,135). However, NGS technology may also have certain disadvantages, such as complex workflow, high rates of variants with uncertain significance, higher cost and the reduction of sensitivity for large insertions/deletions (>20 bp) (136,137). The currently used standard  protocol for the identification of BRCA1 and BRCA2 mutations includes comprehensive sequencing and the assessment of LGRs. Furthermore, a single-site target may also be analyzed for patients with a first-degree relative affected by BRCA1/2 mutation (138,139). The high cost of these technologies has prompted researchers and clinicians to develop novel high-sensitivity and low-cost strategies for the detection of BRCA1/2 mutations. Among these, reliable results were obtained by using the droplet digital PCR (ddPCR) platform.
ddPCR has recently emerged as a reliable tool with high sensitivity and specificity. In brief, the ddPCR system is based on a water-oil emulsion of the reaction mixture, which consists of a DNA sample, ddPCR Mastermix, primers and probe in a final volume of 20 µl (140). This procedure allows division of the sample into ~20,000 droplets that are transferred into a 96-well PCR plate for amplification. Since the sample is fractioned into thousands of droplets, PCR amplification takes place in each droplet. A droplet reader then detects the positive/negative signal of droplets depending on their amplified target and fluorescence amplitude (141).
Of note, ddPCR represents a valuable alternative to standard methods for the analysis of different clinical samples, such as fresh tumor biopsies and formalin-fixed paraffin-embedded (FFPE) tissues, as well as liquid biopsy samples (peripheral blood, sputum, urine, cerebrospinal fluid, stool, pleural effusions and ascites fluid), overcoming the limits due to poor DNA quality (142). Over the years, the potential clinical application of ddPCR has been demonstrated for absolute allele quantification, viral load quantification, DNA methylation, DNA copy number variation, germline/somatic mutation detection, circulating mutation detection, analysis of microRNAs, long non-coding RNAs and gene rearrangements (143)(144)(145)(146)(147). In this field, a growing number of recent studies have focused on the ddPCR system as a promising tool for the identification of specific BRCA1/2 mutations.
Preobrazhenskaya et al (148) developed a ddPCR assay to investigate BRCA1 LGRs in blood-derived DNA samples of patients with breast cancer (n=141). Using ribonuclease P RNA component H1 as a reference gene and PCR primers covering the entire coding region of BRCA1, the researchers identified three cases with exon 8 deletion and one case with exons 5-7 deletion (148). Furthermore, they identified a total of four cases with exon 8 deletion in an additional cohort of patients with breast and ovarian cancer (720 and 184, respectively). Collectively, the ddPCR data exhibited high concordance with multiplex ligation-dependent probe amplification (MLPA), a standard method for the detection of LGRs, suggesting that ddPCR may be a valuable tool for the assessment of BRCA1 LGRs (149). Similarly, another study evaluated the sensitivity and specificity of ddPCR to detect BRCA1 rearrangements in patients with serous ovarian cancer (149). In brief, the authors performed a multiplex ddPCR assay dividing primers/probe for BRCA1 exons into 8 groups along with albumin or ribonuclease P/MRP subunit P30 as a reference gene and identified nine cases with different BRCA1 deletions (100% concordance with MLPA) (149). Of note, Khalique et al (150) provided a case report of high-grade serous ovarian cancer (HGSOC) with secondary somatic mutation of BRCA2 (c.5446_5449delCTAG, p.Ser1816Leu fs*23). Specifically, the study highlighted that the ddPCR assay detected a higher mutation frequency (9.4%) in FFPE tissue samples compared to the whole-exome sequencing genetic test (2.3%) (150). Recently, De Paolis et al (151) further investigated the specificity of ddPCR in a cohort of patients with HGSOC positive for BRCA1 LGRs (exons 2, 20 and 21). By using ribosomal protein lateral stalk subunit P0 as a reference gene and specific primers/probe, the ddPCR assay confirmed the detection of BRCA1 LGRs in blood, FFPE and fresh frozen tissue samples with 100% specificity (151).
Although no studies have been performed on the use of ddPCR for the detection of specific BRCA mutations in relatives of BRCA-positive cancer patients, the use of ddPCR for the detection of already known mutations in familial clusters would reduce the higher costs related to the whole sequencing of both BRCA1 and BRCA2 genes. Indeed, at present, the cost of a single test for the detection of BRCA mutations is 172$, while Garcia and colleagues described that the analysis of gene mutations performed by ddPCR cost half as much as NGS or other methods (152,153).
Besides the cost-effectiveness, ddPCR may also be used for the detection of circulating BRCA1/2 mutations in liquid biopsy samples. Indeed, ddPCR was effectively used for the detection of circulating mutations in patients with ovarian cancer, demonstrating how the detection of both germline and somatic ctDNA mutations is a valuable complementary tool for the diagnosis of BRCA-positive tumors and to establish the effectiveness of PARP inhibitors and the prognosis of patients with ovarian cancer (154).
All of these data suggest that ddPCR may be used for the detection of already known BRCA1/2 mutations in familial clusters of patients with a diagnosis of hereditary breast or ovarian cancer.
In conclusion, BRCA1 and BRCA2 germline mutations are well-established risk factors for the onset of breast or ovarian cancer. Overall, the computational investigations performed in the present study suggested that the BRCA1/2 mutations with the highest number of entries are classified as certainly pathogenic variants, such as 185delAG, 5382insC and C61G for BRCA1 and 6174delT for BRCA2. Furthermore, several of these mutations, also known as founder mutations, appear to be more frequently detected in specific geographical regions and ethnic groups. In this context, the development of low-cost and reliable genetic tests is fundamental to improve the screening program for the identification of females with germline BRCA1/2 mutations and the management of relatives of patients with a known diagnosis of hereditary breast or ovarian cancer. Currently, NGS is the gold standard for the assessment of BRCA1/2 mutations. In this field, ddPCR has recently emerged as a highly sensitive and specific technique. According to the studies described in the present article, ddPCR may be considered a promising alternative strategy for the detection of BRCA1/2 pathogenetic mutations. However, further studies should be performed to validate the application of ddPCR in routine clinical practice and surveillance strategies for hereditary female tumors.

Funding
This work was supported by the Italian League Against Cancer (LILT) -Grant Ricerca Sanitaria 2018 LILT.

Availability of data and materials
The data reported in the manuscript are available from the corresponding author on request. The original data examined in the study are publicly available and may be retrieved from the following sources: www.pubmed.com; https://www.ncbi. nlm.nih.gov/clinvar/; https://research.nhgri.nih.gov/bic/; and https://brcaexchange.org/.

Authors' contributions
ML and AS conceptualized the study. AL, RR, GG and SC wrote the original draft of the manuscript. ML, AS, GNZ, GC and LF provided critical revisions. AL and RR prepared the tables and figures, conducted the formal analysis and critically analyzed the literature. All authors contributed to manuscript revision and read and approved the final version of the manuscript.

Ethics approval and consent to participate
Not applicable.

Patient consent for publication
Not applicable.